Thermodynamically Favorable Reactions Shape the Archaeal Community Affecting Bacterial Community Assembly in Oil Reservoirs
Abstract Background: Microbial communities exist everywhere on the earth, and play essential roles in biogeochemical cycling in all ecosystems. Understanding microbial community assembly mechanisms could improve our ability to manage microbial ecosystems for industrial, pharmaceutical, and agricultural applications. Previous studies have shown that microbial communities are shaped by deterministic or stochastic processes, but how these two processes influence the microbial community together is rarely investigated, especially in deep terrestrial ecology. Methods: Here, the microbial compositions in the production waters collected from water injection wells and oil production wells across eight oil reservoirs throughout northern China were determined using high-throughput 454 pyrosequencing of 16S rRNA genes, and analyzed by proportional distribution analysis and null model analysis. Results: In the study, a ‘core’ microbiota consisting of three bacterial genera and eight archaeal genera were found to be existent in all production water samples. Canonical correlation analysis reflected that these core archaea were significantly influenced by the abiotic factors of temperature and reservoir depth, while the core bacteria were affected by the combined impact of the core archaea and environmental factors. Considering that two of the core archaeal genera, acetoclastic methanogens and hydrogenotrophic methanogens, were enriched in low- and high-temperature oil reservoirs, respectively, it was proposed that the archaeal communities in oil reservoirs were characterized by thermodynamic constraints. Conclusions: Together, our study indicates that microbial community structures in wells of oil reservoirs are originally determined by the thermodynamic conditions, through which the core archaeal communities are shaped directly followed by the deterministic recruiting of core bacterial genera, and then the stochastically selection of some other microbial members from local environments.